code: def freq_bands(
      num_bands: int,
      temperature: float = 10000.0,
      step: int = 2,
      dtype: torch.dtype = torch.float32,
      device: Optional[torch.device] = None,
  ) -> torch.Tensor:
      bands = 1.0 / (
          temperature
          ** (
              torch.arange(
                  0, num_bands, step, dtype=dtype, device=device
              )
              / num_bands
          )
      )
      return bands
  
imports: import math
  from typing import List, Tuple, Optional, Union
  import torch
  from torch import nn
  from .trace_utils import _assert
label_desc: Use image node_id 2 for calling a global function with example usage: freq_bands(num_bands, temperature, step, dtype, device) and returns: bands